A normative database of free-breathing thoracic 4D dynamic MRI images and associated regional respiratory parameters of healthy children

Yubing Tong; Jayaram K. Udupa; Joseph M. McDonough; Caiyun Wu; Yusuf Akhtar; Lipeng Xie; Mostafa Alnoury; Mahdie Hosseini; Leihui Tong; Samantha Gogel; David M. Biko; Oscar H. Mayer; Jason B. Anari; Drew A. Torigian; Patrick J. Cahill

doi:10.1117/12.3006807

2 April 2024 A normative database of free-breathing thoracic 4D dynamic MRI images and associated regional respiratory parameters of healthy children

Yubing Tong, Jayaram K. Udupa, Joseph M. McDonough, Caiyun Wu, Yusuf Akhtar, Lipeng Xie, Mostafa Alnoury, Mahdie Hosseini, Leihui Tong, Samantha Gogel, David M. Biko, Oscar H. Mayer, Jason B. Anari, Drew A. Torigian, Patrick J. Cahill

Author Affiliations +

Proceedings Volume 12931, Medical Imaging 2024: Imaging Informatics for Healthcare, Research, and Applications; 1293111 (2024) https://doi.org/10.1117/12.3006807
Event: SPIE Medical Imaging, 2024, San Diego, California, United States

Abstract

In pediatric patients with respiratory abnormalities, it is important to understand the alterations in regional dynamics of the lungs and other thoracoabdominal components, which in turn requires a quantitative understanding of what is considered as normal in healthy children. Currently, such a normative database of regional respiratory structure and function in healthy children does not exist. The purpose of this study is to introduce a large open-source normative database from our ongoing Virtual Growing Child (VGC) project, which includes measurements of volumes, architecture, and regional dynamics in healthy children (six to 20 years) derived via dynamic Magnetic Resonance Imaging (dMRI) images. The database provides four categories of regional respiratory measurement parameters including morphological, architectural, dynamic, and developmental. The database has 3,820 3D segmentations (around 100,000 2D slices with segmentations), which to our knowledge is the largest dMRI dataset of healthy children. The database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters for healthy children. The database can serve as a reference standard to quantify regional respiratory abnormalities on dMRI in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The database can be useful to advance future AI-based research on MRI-based object segmentation and analysis.

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Yubing Tong, Jayaram K. Udupa, Joseph M. McDonough, Caiyun Wu, Yusuf Akhtar, Lipeng Xie, Mostafa Alnoury, Mahdie Hosseini, Leihui Tong, Samantha Gogel, David M. Biko, Oscar H. Mayer, Jason B. Anari, Drew A. Torigian, and Patrick J. Cahill "A normative database of free-breathing thoracic 4D dynamic MRI images and associated regional respiratory parameters of healthy children", Proc. SPIE 12931, Medical Imaging 2024: Imaging Informatics for Healthcare, Research, and Applications, 1293111 (2 April 2024); https://doi.org/10.1117/12.3006807

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